comparison COBRAxy/custom_data_generator.py @ 395:64563ca68ace draft

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394:a0b53ccc73a8

            raise utils.DataErr(ARGS.model, f"failed loading built-in model: {e}")

    # Determine final model name: explicit --name overrides, otherwise use the model id
    
    model_name = ARGS.name if ARGS.name else ARGS.model
    
    
    if ARGS.name == "ENGRO2" and ARGS.medium_selector != "Default":
        df_mediums = pd.read_csv(ARGS.tool_dir + "/local/medium/medium.csv", index_col = 0)
        ARGS.medium_selector = ARGS.medium_selector.replace("_", " ")
        medium = df_mediums[[ARGS.medium_selector]]

        for reaction, value in medium.items():
            if value is not None:
                model.reactions.get_by_id(reaction).lower_bound = -float(value)

    if ARGS.name == "ENGRO2" and ARGS.gene_format != "Default":
        utils.convert_genes(model, ARGS.gene_format)

    # generate data
    rules = generate_rules(model, asParsed = False)
    reactions = generate_reactions(model, asParsed = False)
    bounds = generate_bounds(model)

395:64563ca68ace

            raise utils.DataErr(ARGS.model, f"failed loading built-in model: {e}")

    # Determine final model name: explicit --name overrides, otherwise use the model id
    
    model_name = ARGS.name if ARGS.name else ARGS.model
    print(ARGS.name)
    print(model_name)
    print(ARGS.medium_selector)
    
    if ARGS.name == "ENGRO2" and ARGS.medium_selector != "Default":
        df_mediums = pd.read_csv(ARGS.tool_dir + "/local/medium/medium.csv", index_col = 0)
        ARGS.medium_selector = ARGS.medium_selector.replace("_", " ")
        medium = df_mediums[[ARGS.medium_selector]]

        for reaction, value in medium.items():
            if value is not None:
                model.reactions.get_by_id(reaction).lower_bound = -float(value)

    if ARGS.name == "ENGRO2" and ARGS.gene_format != "Default":
        model = utils.convert_genes(model, ARGS.gene_format)

    # generate data
    rules = generate_rules(model, asParsed = False)
    reactions = generate_reactions(model, asParsed = False)
    bounds = generate_bounds(model)